1. Field of the Invention
The invention relates to a three-dimensional (3D) imaging sensor and method for controlling an autonomous vehicle.
2. Background of the Invention
In a modern vehicle, the driver remains a critical component of the vehicle's control system as the driver makes numerous decisions directed to the safe operation of the vehicle including speed, steering, obstacle and hazard recognition, and avoidance thereof. Yet, the driver's ability to perform all of these functions can become compromised due to physical factors such as driver fatigue, driver impairment, driver inattention, or other factors such as visibility that reduce the reaction time needed by the driver to successfully avoid hazards.
Furthermore, in environmentally dangerous surroundings such as for example in warfare settings or in settings where toxic or nuclear radiation hazards are present, the driver is at risk. Indeed, roadside bombs in Iraq are just one contemporary example of the loss of human life which could in many situations be avoided if supply trucks bringing materials to the troops were unmanned.
In other more conventional environments, the driver may become disoriented or incapable of physically commanding the vehicle as would occur if the driver suffered a medical emergency or if for example the driver became disoriented under the driving conditions. One example of such a disorienting or incapacitating environment would be a car or ship being driven or steered under snow, fog, rain, and/or nighttime blackout conditions where the diver (or captain of the ship) is handicapped in his or her ability to perceive and react to hazards approaching or to which the ship is approaching.
Thus, whether addressing human deficiencies in the control of a vehicle or whether in environmentally hazardous conditions where human control is not preferred, there exists a need to have a system and method for vehicular identification of objects in the path of the vehicle.
Numerous articles on the development of autonomously driven vehicles and laser detection and visualization systems have been reported such as the following reference articles all of which are incorporated herein by reference:    1) H. Wang, J. Kearney, J. Cremer, and P. Willemsen, “Steering Autonomous Driving Agents Through Intersections in Virtual Urban Environments,” 2004 International Conference on Modeling, Simulation, and Visualization Methods, (2004);    2) R. Frezza, G. Picci, and S. Soatto, “A Lagrangian Formulation of Nonholonomic Path Following,” The Confluence of Vision and Control, (A. S. Morse et al. (eds), Springer Verlag, 1998);    3) J. Shirazi, Java Performance Tuning, (OReilly & Associates, 2000);    4) J. Witt, C. Crane III, and D. Armstrong, “Autonomous Ground Vehicle Path Tracking,” Journal of Robotic Systems, (21(8), 2004);    5) C. Crane III, D. Armstrong Jr., M. Torrie, and S. Gray, “Autonomous Ground Vehicle Technologies Applied to the DARPA Grand Challenge,” International Conference on Control, Automation, and Systems, (2004);    6) T. Berglund, H. Jonsson, and I. Soderkvist, “An Obstacle-Avoiding Minimum Variation B-spline Problem,” International Conference on Geometric Modeling and Graphics, (July, 2003);    7) D. Coombs, B. Yoshimi, T. Tsai, and E. Kent, ‘Visualizing Terrain and Navigation Data,” NISTIR 6720, (Mar. 1, 2001);    8) U.S. Pat. No. 5,644,386 to Jenkins et al;    9) U.S. Pat. No. 5,870,181 to Andressen;    10) U.S. Pat. No. 5,200,606 to Krasutsky et al; and    11) U.S. Pat. No. 6,844,924 to Ruff et al;Despite this work, realization of suitable visualization, obstacle identification, and obstacle avoidance systems and methods has not been without problems limiting the operation of vehicles.